A dynamic photogrammetry system includes two or more cameras that can capture images at a high speed. The cameras synchronously capture images of a target point to be measured. By calibrating projection imaging models of the cameras, spatial light may be restored from image plane points, and spatial coordinates of the point to be measured may be calculated from an intersection of the spatial light. Imaging models of cameras include interior and exterior orientation parameter types. Interior orientation parameters include principal point, principal distance and various distortion parameters of different orders. Exterior orientation parameters include the position and directional angle of the camera in a spatial coordinate system. Finding a solution of the exterior orientation parameter is to perform positioning and orientation of the photogrammetry system.
Currently, it is generally recognized that a self-calibration bundle adjustment method can provide the highest positioning and orientation precision, because this technology considers the influence of the interior orientation parameters on the measurement result during adjustment and the obtained interior and exterior orientation parameter results are optimal results that match the measurement environment and the measurement network. The most commonly used self-calibration methods in the field of stereo vision measurement are Tsai's two-stage calibration method and Zhang Zhengyou's plane calibration method. Commonly used calibration objects include a three-dimensional calibration object, a planar checkerboard calibration plate, a flat dot calibration plate, and so on. The essence of such calibration methods is to generate a measurement network having several control points through relative movement of the calibration object and the camera, so as to implement self-calibration bundle adjustment of a single camera, and then solving an orientation relationship between the two cameras in a same coordinate system.
Such methods have been applied to machine vision, structured light measurement, and high-precision large-scale stereo vision measurement systems. Such self-calibration methods are suitable for small measurement ranges (generally smaller than 1 m*1 m), because the precision and the size of the calibration object are inversely proportional to each other. When such methods are used for structured light measurement in a small space or microscopic measurement, a desirable calibration precision can be obtained.
Such self-calibration methods have the following defects: the focus of the adjustment process is the interior orientation parameter, and there is no direct optimization or evaluation on the orientation relationship between cameras; coordinate precision of target points on the calibration plate that are used as control points leads to a system error; differences between the target points on the calibration plate and the measurement points in material and imaging quality lead to a system error; in addition to the image plane error or spatial coordinate error estimation, there is no reliable objective spatial evaluation indicators. Therefore, such method are not suitable for large-scale measurement occasions having high requirements on precision and precision traceable.